Designing seeds for similarity search in genomic DNA

  • Authors:
  • Jeremy Buhler;Uri Keich;Yanni Sun

  • Affiliations:
  • Washington University, St. Louis, MO;University of California - San Diego, La Jolla, CA;Washington University, St. Louis, MO

  • Venue:
  • RECOMB '03 Proceedings of the seventh annual international conference on Research in computational molecular biology
  • Year:
  • 2003

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Abstract

Large-scale comparison of genomic DNA is of fundamental importance in annotating functional elements of genomes. To perform large comparisons e.ciently, BLAST [3, 2] and other widely used tools use seeded alignment, which compares only sequences that can be shown to share a common pattern or "seed" of matching bases. The literature suggests that the choice of seed substantially affects the sensitivity of seeded alignment, but designing and evaluating seeds is computationally challenging. This work addresses problems arising in seed design. We give the fastest known algorithm for evaluating the sensitivity of a seed in a Markov model of ungapped alignments, as well as theoretical results on which seeds are good choices. We also describe Mandala, a software tool for seed design, and show that it can be used to improve the sensitivity of alignment in practice.